Browse Articles

Peptidoglycan-reshuffling proteins SCO0954, SCO1758, SCO4439, and SCO4440 modulate the formation of wall-deficient cells in Streptomyces coelicolor under hyperosmotic sucrose stress

Abstract Streptomycetes are biotechnologically valuable bacteria with complex cell division that produce extracellular vesicles (EVs), typically nanometre-sized but can reach 2.5 μm in diameter. Streptomyces also produce dividing wall-deficient L-forms (0.5–7 μm diameter) and, under hyperosmotic stress, non-dividing wall-deficient S-cells (3–4 μm diameter). The boundaries between EVs, L-forms and S-cells are not always clear, as large DNA-containing EVs can resemble small L-forms and S-cells in size. Both EVs and wall-deficient cells offer competitive advantages, such as inter-bacterial signalling, antibiotic transport, resistance and phage defence. However, their formation mechanisms remain poorly understood. We identified sco1758 (engA GTPase), sco0954 (methionine N-acetyltransferase), sco4439 (D-Ala-D-Ala carboxypeptidase), and sco4440 (GOLPH3-like) as important for wall-deficient cell formation in Streptomyces coelicolor under hyperosmotic sucrose conditions. Mutations in sco4439 and sco4440 increased tetra–tetra(Gly) and tetra(Gly)–penta(Gly) (4–3) peptidoglycan (PG) dimers, while sco1758 affected only the former. Complementation reversed these changes. sco0954 overexpression enhanced PG-associated methionine acetylation and oxidation. Our findings suggest that PG dimerisation and methionine modification may contribute to the formation of wall-deficient cells under hyperosmotic sucrose stress. Further research is required to elucidate how SCO1758, SCO0954 and SCO4439/40 modulate PG architecture and to evaluate their potential to promote EV production for biotechnological applications.

Benchmarking of dimensionality reduction methods to capture drug response in transcriptome data

Knowledge attitudes and practices regarding the use of prebiotics and probiotics for respiratory infections among Saudi healthcare students

Generative AI: a generation-defining shift for biopharma regulatory affairs

A Deep Learning and Explainable Artificial Intelligence based Scheme for Breast Cancer Detection

Experimental study on improving the durability of underground/underwater structures by mixing impregnating agents into unhardened concrete

Abstract Components exposed to soil and water are difficult to maintain during their service life, and have traditionally been designed to ensure greater durability than components exposed to air. However, in recent years, severe damage caused by aging has also been observed in components exposed to soil and water, prompting the development of methods to achieve higher durability. To address this issue, the authors developed a method (mixing method) that enhances the durability of concrete components by mixing sodium silicate-based impregnation materials with fresh concrete. In this study, the flowability, deterioration inhibition effects, and mechanical properties of concrete prepared using the mixing method were experimentally confirmed. The results demonstrated that by controlling the addition of the impregnation material, it is possible to achieve deterioration suppression effects equivalent to or superior to those of conventional methods without significantly reducing the workability or mechanical properties. In addition, an equation for estimating the mechanical properties expressed from the amount of admixture was proposed. Based on the results of this study, it is considered that the mixing method can be applied as a method for maintaining and improving the durability of concrete structures. In order to put this into practical use, it is necessary to conduct experiments under a wider range of conditions to improve the accuracy of estimating the deterioration suppression effect and the characteristics that appear, and to expand the range of applications.

Design of Tough 3D Printable Elastomers with Human‐in‐the‐Loop Reinforcement Learning

Abstract The development of high‐performance elastomers for additive manufacturing requires overcoming complex property trade‐offs that challenge conventional material discovery pipelines. Here, a human‐in‐the‐loop reinforcement learning (RL) approach is used to discover polyurethane elastomers that overcome pervasive stress–strain property tradeoffs. Starting with a diverse training set of 92 formulations, a coupled multi‐component reward system was identified that guides RL agents toward materials with both high strength and extensibility. Through three rounds of iterative optimization combining RL predictions with human chemical intuition, we identified elastomers with more than double the average toughness compared to the initial training set. The final exploitation round, aided by solubility prescreening, predicted twelve materials exhibiting both high strength (>10 MPa) and high strain at break (>200%). Analysis of the high‐performing materials revealed structure‐property insights, including the benefits of high molar mass urethane oligomers, a high density of urethane functional groups, and incorporation of rigid low molecular weight diols and unsymmetric diisocyanates. These findings demonstrate that machine‐guided, human‐augmented design is a powerful strategy for accelerating polymer discovery in applications where data is scarce and expensive to acquire, with broad applicability to multi‐objective materials optimization.

A disproportionality analysis of real-world adverse events associated with tirofiban from the FAERS database

Heterogeneity-optimized method for predicting immune checkpoint blockade response

Pregnancy outcomes following fluoroscopy-guided tubal recanalization: a comparison of spontaneous conception and intrauterine insemination—a retrospective cohort study

Abstract To evaluate and compare pregnancy outcomes following successful fluoroscopy-guided tubal recanalization (FGTR), focusing on spontaneous conception versus intrauterine insemination (IUI). This retrospective cohort study included 139 women aged 21–40 years who underwent FGTR for tubal occlusion between January 2021 and May 2024. After exclusions, 80 women attempted natural conception, and 59 underwent IUI with ovarian stimulation. Groups were compared in terms of clinical pregnancy rates, time to conception, and post-procedure tubal patency. Clinical pregnancy rates were similar between spontaneous conception (51.2%) and IUI (57.6%) groups (p = 0.976). Mean time to conception did not differ significantly (6.4 ± 2.8 vs. 5.9 ± 2 months, p = 0.360). No pregnancies occurred in women with bilateral distal obstruction, whereas proximal occlusions (unilateral or bilateral) were associated with higher pregnancy rates. Six-month follow up HSG demonstrated that bilateral tubal patency correlated with greater conception likelihood. In women with tubal factor infertility who achieve patency after FGTR, spontaneous conception and IUI yield comparable pregnancy outcomes and similar time to conception. Expectant management may be a cost-effective first-line approach, reserving IUI or IVF for cases without conception within a reasonable timeframe. The site of tubal obstruction and patency status should guide individualized post-FGTR fertility planning.

Psychometric validity of the Perceived Home Management Hassles Scale

Effect of heat treatment on the microstructure and mechanical properties of CX stainless steel fabricated by selective laser melting

Study of the impact of citizens’ perceived behavioral control on waste littering behavior and the resulting environmental status

Conditional Stabilization of the Hypoxia‐Inducible Factor HIF1α— Photoswitchable Stapled Peptides Prevent Elongin BC–Mediated Degradation

Abstract Oxygen levels and its distribution are tightly regulated due to their critical impact on health. Hypoxia‐inducible factors (HIFs) are traditionally recognized as key regulators of the transcriptional response to low oxygen (hypoxia). Recent research expanded their functions, highlighting their potential as therapeutic targets. Despite these advances, there is still a need for chemical biology tools that offer precise spatiotemporal control within the HIF network and output. Here, we introduce an optochemical approach that enables significant differences in expression of HIF1α‐target genes depending on the photostationary state (PSS). Our photoswitchable stapled peptide PS B ‐BCB‐04 stabilized HIF1α under normoxic conditions by targeting EloBC ( k i   =  7.9 ± 1.3 nM) and preventing VHL‐mediated degradation. Visible light allowed reversible regulation of peptide conformation, which entailed a sevenfold difference in its EloBC‐binding capacity. In a proof‐of‐concept study, we demonstrated that inhibition of HIF1α degradation enabled isomer‐specific expression of the vascular endothelial growth factor (VEGFA) in prostate cancer cells. Our results validated the potential of photopharmacological stabilization of HIF1α and provided a new toolbox for on‐demand photocontrol over the HIF‐signaling pathway as well as VHL‐mediated degradation.

A deception detection model by using integrated LLM with emotion features

Interpretable AI-assisted diagnosis of papillary thyroid cancer cytopathology using graph neural networks and knowledge graphs

Abstract This study presents an interpretable AI-assisted diagnostic approach for papillary thyroid carcinoma (PTC) cytopathology by combining graph neural networks (GNNs) with knowledge graphs (KGs). Routine cytology smears from 281 PTC cases were scanned, labeled, and processed using the Cascade RCNN model to detect pathological cell features, including 45,680 ground-glass nuclei, 712 nuclear grooves, and 116 intranuclear inclusions. By integrating GNNs, the model achieved a mean intersection over union (mIoU) of 56.14% and a mean average precision (mAP) of 0.87. The GINet model further improved classification accuracy to 88.84%. Our approach also incorporates a clinical decision support system (CDSS) for querying KGs, providing explainable diagnostic outputs. This method offers an interpretable and reliable AI tool for PTC diagnosis, enhancing the transparency of AI-assisted pathology systems.

Establishing 3 <i>d</i> –4 <i>d</i> Orbital Hybridization for Efficient Photothermal Catalytic CO ₂ Hydrogenation

Abstract Photothermal catalytic CO 2 conversion offers a promising way to address the energy and environmental issues; however, the development of self‐supporting catalysts with high activity and selectivity remains a great challenge. Here, we report the decoration of PdCo alloy on self‐supporting carbon cloth with N‐doped carbon arrays (PdCo‐NC/CC) for efficient photothermal catalytic methanation. In situ spectra and density function theoretical (DFT) calculations demonstrate that the 3 d ‐4 d hybridization between Co and Pd enables an increase in the energy level of the dz 2 ‐5 σ and dyz ‐2 π* states in the CO/PdCo alloy, thus enhancing the binding strength of the *CO intermediate and accelerating the CO hydrogenation. Specifically, the self‐supporting substrate provides highly dispersed metal sites for CO 2 methanation while serving as a photo‐to‐heat converter to improve the temperature of the reaction system. As a result, PdCo‐NC/CC exhibits unprecedented photothermal performance toward CO 2 methanation, delivering a CH 4 generation rate as high as 15.23 mol g metal −1  h −1 and a selectivity of 100% in batch reaction under the irradiation of Xenon lamp without any external thermal source. Moreover, the continuous flow photothermal reaction can be smoothly proceeded over 100 h, demonstrating the high stability of PdCo‐NC/CC in CO 2 hydrogenation.

Improved optical characteristics of PEO polymer integrated with graphene oxide

C(sp ² )─H Bond Activation with a Heterometallic Nickel–Aluminium Complex

Abstract Herein we present a ligand‐catalyzed bond‐breaking and making process that occurs with a Ni–Al heterometallic complex. While combinations of Ni pre‐catalysts and Al additives are known for site‐selective C─H functionalization, detailed studies of such systems are rare. Combining [Ni(COD) 2 ] and [(BDI)AlH 2 ] ( 1 ; BDI = 2,6‐diisopropylphenyl‐β‐methyldiketiminate) results in facile formation of a Ni–Al heterometallic complex [( η 4 ‐COD)Ni{( μ ‐H) 2 Al(BDI)}] ( 2 ; COD = 1,5‐cyclooctadiene). Once generated, this species can effect the C(sp 2 )─H activation of 4‐dimethylaminopyridine (DMAP) or pyridine with concomitant H 2 evolution, a process that is accelerated through addition of PCy 3 . The mechanism was studied through kinetics, kinetic isotope effects (KIEs), isotope labeling studies, and modeling. The reaction is 1 st order in PCy 3 and proceeds with a KIE of 0.9–1.1. Support is provided for a pathway involving the synergistic action of both metals, promoted by reversible coordination of the phosphine. The data suggest that both C─H oxidative addition and H 2 reductive elimination steps in this system are readily accessible and are not rate limiting. This finding has implications for future catalyst design using combinations of Ni and Al metals and suggests that control of ligand exchange steps may be the most important consideration in determining the rate of reaction.

The gut microbiome as a target in cancer immunotherapy: opportunities and challenges for drug development